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Derivative-free & order-robust optimisation

Abstract : In this paper, we formalise order-robust optimisation as an instance of online learning minimising simple regret, and propose VROOM, a zeroth order optimisation algorithm capable of achieving vanishing regret in non-stationary environments, while recovering favorable rates under stochastic reward-generating processes. Our results are the first to target simple regret definitions in adversarial scenarios unveiling a challenge that has been rarely considered in prior work.
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https://hal.inria.fr/hal-03288939
Contributor : Michal Valko Connect in order to contact the contributor
Submitted on : Friday, July 16, 2021 - 3:42:02 PM
Last modification on : Friday, November 5, 2021 - 4:12:29 PM
Long-term archiving on: : Sunday, October 17, 2021 - 6:51:26 PM

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  • HAL Id : hal-03288939, version 1

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Victor Gabillon, Rasul Tutunov, Michal Valko, Haitham Bou Ammar. Derivative-free & order-robust optimisation. International Conference on Artificial Intelligence and Statistics, Aug 2020, Palermo / Virtual, Italy. ⟨hal-03288939⟩

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